The inflammation-nutrition score supports the prognostic prediction of the TNM stage for colorectal cancer patients after curative resection.

PURPOSE: Inflammation and the nutritional and immunologic status are known to be associated with the prognosis of malignant tumors. We aimed to examine inflammation-nutrition scores and predict the prognosis of colorectal cancer (CRC) patients by integrating nutritional and immunologic factors and tumor stage. METHODS: This study investigated 511 patients with CRC from 2007 to 2013: 380 in a training set (TS) and 131 in a validation set (VS). The Osaka Prognostic Score (OPS) used comprised 1 point each for C-reactive protein > 1.0 mg/dL, albumin (< 3.5 g/dL), and lymphocyte count < 1600. Patients were classified according to the total points. The modified Glasgow Prognostic Score and the Prognostic Nutritional Index were also examined. A nomogram for predicting the disease-free survival (DFS) and overall survival (OS) was constructed based on the OPS and TNM stage. RESULTS: In the TS, a high OPS and high TNM stage were significant predictors of the DFS and OS. The C-indexes of the OPS for the DFS and OS were higher than those of other reported scoring systems. The C-index of the nomogram for the DFS was 0.762 in the TS and 0.675 in the VS. The C-index of the nomogram for the OS was 0.805 in the TS and 0.743 in the VS. CONCLUSION: Integrating the TNM stage and OPS accurately predicted the prognosis of patients with CRC.

Erratum: A novel prognostic prediction model for recurrence in patients with stage II colon cancer after curative resection.

[This corrects the article DOI: 10.3892/mco.2018.1733.].

A novel prognostic prediction model for recurrence in patients with stage II colon cancer after curative resection.

The present study aimed to clarify the risk factors for recurrence of stage II colon cancer in patients and to determine possible treatment options for postoperative adjuvant chemotherapy. A prediction model for recurrence in patients with stage II colon cancer after curative surgical resection was developed. The present study retrospectively investigated 436 patients who underwent curative resection for stage II colon cancer at Osaka International Cancer Institute and Yao Municipal Hospital between 2004 and 2012. Several clinicopathological factors were examined and the Cox regression model was used to develop a prediction model for recurrence. The prediction model was validated in an independent group of 213 patients who underwent surgery at Osaka University Hospital between 2001 and 2012. Univariate analysis revealed that preoperative serum carcinoembryonic antigen level, preoperative obstruction, tumor invasion, lymphatic invasion and venous invasion were significantly correlated with disease-free survival. Using these variables, a classification and regression tree was constructed as a prediction model. The prediction models were validated by external datasets in an independent patient group. The concordance indices for DFS after current surgical resection were 0.675 in the learning set and 0.552 in the validation set. To conclude, a novel, reliable and personalized prognostic model was developed to predict recurrence in patients with stage II colon cancer, which may help clinicians to determine and perform adjuvant chemotherapy.